International Journal of Biometeorology

, Volume 61, Issue 8, pp 1481–1492 | Cite as

Examination of climatological wind patterns and simulated pollen dispersion in a complex island environment

  • Brian J. Viner
  • Raymond W. Arritt
  • Mark E. Westgate
Original Paper
First Online:
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Revised:
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Abstract

Complex terrain creates small-scale circulations which affect pollen dispersion but may be missed by meteorological observing networks and coarse-grid meteorological models. On volcanic islands, these circulations result from differing rates of surface heating between land and sea as well as rugged terrain. We simulated the transport of bentgrass, ryegrass, and maize pollen from 30 sources within the agricultural regions of the Hawaiian island Kaua’i during climatological conditions spanning season conditions and the La Niña, El Niño, and neutral phases of the El Niño-Southern Oscillation. Both pollen size and source location had major effects on predicted dispersion over and near the island. Three patterns of pollen dispersion were identified in response to prevailing wind conditions: southwest winds transported pollen inland, funneling pollen grains through valleys; east winds transported pollen over the ocean, with dispersive tails for the smallest pollen grains following the mean wind and extending as far as the island of Ni’ihau 35 km away; and northeast winds moved pollen inland counter to the prevailing flow due to a sea breeze circulation that formed over the source region. These results are the first to predict the interactions between complex island terrain and local climatology on grass pollen dispersion. They demonstrate how numerical modeling can provide guidance for field trials by illustrating the common flow regimes present in complex terrain, allowing field trials to focus on areas where successful sampling is more likely to occur.

Keywords

Atmospheric dispersion Atmospheric modeling Sea breeze Zea mays Agrostis sp. Lolium sp. 
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Notes

Acknowledgements

This project was supported by Biotechnology Risk Assessment Program grant numbers 20073921118473 and 20093352205804 from the US Department of Agriculture’s National Institute of Food and Agriculture (NIFA). Computing resources were funded by an endowment to the Department of Agronomy at Iowa State University. We thank Daryl Herzmann for computing assistance.

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Copyright information

© ISB 2017

Authors and Affiliations

  • Brian J. Viner
    • 1
  • Raymond W. Arritt
    • 2
  • Mark E. Westgate
    • 2
  1. 1.Atmospheric Technologies GroupSavannah River National LaboratoryAikenUSA
  2. 2.Department of AgronomyIowa State UniversityAmesUSA

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